摘要
The striping pattern nonuniformity of the infrared line scanner （IRLS） severely limits the system performance. An adaptive nonuniformity correction （NUC） algorithm for IRLS using neural network is proposed. It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.
The striping pattern nonuniformity of the infrared line scanner （IRLS） severely limits the system performance. An adaptive nonuniformity correction （NUC） algorithm for IRLS using neural network is proposed. It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.
基金
This work was supported by the Pre-Research Foundation of National Defense under Grant No. 30404.
